FORECASTS WEEK METHOD 1 METHOD 2 ACTUAL DEMAND 1 0.90 0.80 0.70 1.05 1.20 o 1.00 3 0.95 0.90 1.00 1.20 1.11 1.00 2.

A forecast for the first six months of the year revealed a tendency to underpredict the actual demand for the revitalized Hubig’s Pies plant in the Marigny.   Month Actual Forecast January 675 600 February 720 700 March 640 620 April 510 495 May 480 410 June 565 535 ​ What is the mean squared error of this forecast?   a. 1,694   b. 1,873   c. 2,075   d. 1,469

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Help Saved Mary, Susan, and Sarah are running a beach boutique on the board walk of Ocean City. Their favorite product is a red lifeguard hoody. Mary believes it will sell 318 times next season. Susan forecasts sales of 518, and Sarah forecasts 199. What would be the result of a simple forecast combination? (Round to two decimal places)

The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 Week Of a) The forecasted demand for the week of October 12 using a 3-week moving average = pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.10, 0.35, and 0.55, using 0.55 for the most recent week, the forecasted demand for the week October 12 pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.) c) If the forecasted demand for the week of August 31 is 360 and a = 0.20, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). August 31 September 7 September 14 September 21…

Asvnch Problem - Statistical Forecasting Data Set – Eunice BC Fashion Monthly Sales, in million units. Year Total Sales Year Total Sales 2010 38 2016 43 2011 41 2017 40 2012 40 2018 45 2013 45 2019 47 2014 50 2020 42 2015 42 2021 48 Questions: a. Find the naïve forecast. b. Use the 3 years moving average forecast. c. Have a 5 years weighted moving average. d. Develop forecast using exponential smoothing with a = 0.2. e. Determine the trend line equation and present the forecast. f. Find the best forecast for year 2022. Note: Use the first 5 years as the training samples and the last 5 years as the forecasting samples. Solve it in Excel Sheet/Sheet with Equations as possible.

ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows:    Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using a five-month moving average approach.

a. What is the mean square error for time periods 2 through 4 using the average forecasting method? b. What is the mean absolute error for time periods 2 through 4 using the average forecasting method? c. What is the mean absolute percentage error for time period 2 through 4 using the average forecasting method? Round all answers to two decimal places. Time Period 1 2 3 4   Mean absolute error (MAE) Mean squared error (MSE) Mean absolute percentage error (MAPE) Electric Bill 510 315 420 480                           Average Forecast                 Forecast Error

The following table gives the number of pints of type A blood used at Woodlawn Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 - a) The forecasted demand for the week of October 12 using a 3-week moving average = pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.10, 0.30, and 0.60, using 0.60 for the most recent week, the forecasted demand for the week of October 12 = pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.) Week Of c) If the forecasted demand for the week of August 31 is 360 and a = 0.20, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). August 31 September 7 September 14…

The Toro Cutlery Company has collected monthly sales information below: MONTH January February March April The company is examining two forecasting methods, moving average and exponential smoothing for forecasting sales. a. What will the forecast be for January the following year using a three-, four-, and five-month moving averages? Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast (January, 3-month MA): 87667 Forecast (January, 4-month MA): 72500 Forecast (January, 5-month MA): 69600 b. What will the forecast be for January the following year using exponential smoothing with a = 0.6? Assume the forecast for February this year is 25,000. Do not round intermediate calculations. Round your answer to the nearest whole number. SALES 25,000 18,000 43,000 110,000 MONTH May June July August SALES MONTH 84,000 September 28,000 October 97,000 November 58,000 December SALES 27,000 105,000 82,000 76,000